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Data Collection Engineer Jobs in California (NOW HIRING)

Data Engineer

Sunnyvale, CA · On-site

$150K - $450K/yr

The Role As a Data Engineer specializing in Natural Language Processing (NLP) and large-scale data ... Document data collection methodologies, dataset characteristics, and pipeline architecture clearly ...

Software Engineer, RL Data

San Francisco, CA

$134K - $162K/yr

Build data collection pipelines, read the transcripts they produce, and iterate on prompts, evals ... Strong software engineering skills in at least one modern programming language - we mostly use ...

The Data Engineering team within the MGC organization plays a critical role in supporting data-driven analytics by providing data collection, warehousing, and analytics at big data scale. Our team ...

Software Engineer, RL Data

San Francisco, CA · On-site

$134K - $162K/yr

Build data collection pipelines, read the transcripts they produce, and iterate on prompts, evals ... Strong software engineering skills in at least one modern programming language - we mostly use ...

Data Engineer in Sunnyvale CA

Sunnyvale, CA · On-site

$134K - $161K/yr

Engineers will write data collection scripts, aggregation algorithms, and implement storage technologies that power our internal business intelligence operations. Candidates are expected to be ...

Data Engineer, iOS - Health Technologies

San Diego, CA · On-site

$121K - $146K/yr

We have an opportunity for a highly capable Data Engineer to join our multidisciplinary Software ... Collaborate cross-functionally to understand data collection and consumption needs that support ...

Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

The Data Engineering team within the MGC organization plays a critical role in supporting data-driven analytics by providing data collection, warehousing, and analytics at big data scale. Our team ...

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Showing results 1-20

Data Collection Engineer information

See California salary details

$50.8K

$145.5K

$194.4K

How much do data collection engineer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for data collection engineer in California is $145,530.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,900.00 and $193,400.00 per year, depending on experience, location, and employer.

What are some common challenges Data Collection Engineers face when gathering and managing large-scale datasets?

Data Collection Engineers frequently encounter challenges such as ensuring data quality and consistency across various sources, managing the volume and velocity of incoming data, and handling data privacy or compliance concerns. They must also design robust pipelines that can scale as data needs grow, and often collaborate with data scientists, software engineers, and product teams to align data collection strategies with project goals. Regularly troubleshooting data ingestion errors and adapting to changing data requirements are also key parts of the role.

What is the difference between Data Collection Engineer vs Data Analyst?

AspectData Collection EngineerData Analyst
Primary FocusDesigning and implementing data collection systems and pipelinesAnalyzing and interpreting data to support business decisions
Skills & CertificationsData engineering, SQL, programming (Python, Java), data architectureStatistical analysis, data visualization, SQL, Excel
Work EnvironmentData engineering teams, IT infrastructure, cloud platformsBusiness units, analytics teams, reporting tools

While Data Collection Engineers focus on building and maintaining data pipelines and infrastructure, Data Analysts interpret the collected data to generate insights. Both roles often collaborate but serve different stages of the data lifecycle, with the engineer ensuring data availability and the analyst deriving actionable insights.

What are Data Collection Engineers?

Data Collection Engineers are professionals who design, implement, and maintain systems for gathering data from various sources. Their work involves creating pipelines to collect, store, and preprocess data, often in support of analytics, machine learning, or business intelligence projects. They work closely with data scientists and software engineers to ensure data quality and reliability. Data Collection Engineers may use a range of tools and technologies, such as APIs, web scraping frameworks, and database management systems, to automate and optimize data acquisition processes.

Is AI replacing data engineers?

AI is transforming the role of data collection engineers by automating certain tasks such as data preprocessing and integration, but it does not fully replace the need for human expertise in designing data pipelines, managing data quality, and ensuring system reliability. Data engineers continue to be essential for building and maintaining the infrastructure that supports AI and machine learning models. Skills in programming, database management, and cloud platforms remain critical in this evolving field.

What engineers make $500,000?

Senior data collection engineers or related roles in data engineering, machine learning, and AI often reach or exceed $500,000 annually, especially with extensive experience, advanced skills in cloud platforms, and leadership responsibilities. Compensation varies by industry, location, and company size, with some positions offering bonuses and stock options that contribute to total earnings.

What engineers make $300,000 a year?

Senior data collection engineers, especially those with extensive experience, advanced skills in data systems, and expertise in tools like SQL, Python, or cloud platforms, can earn $300,000 or more annually. High compensation is often associated with roles in large organizations, specialized industries, or positions requiring leadership and strategic oversight.

What are the key skills and qualifications needed to thrive as a Data Collection Engineer, and why are they important?

To thrive as a Data Collection Engineer, you need a solid background in computer science or engineering, experience with data acquisition, and proficiency in programming languages like Python or Java. Familiarity with data collection frameworks, APIs, sensor technologies, and cloud platforms is commonly required, along with certifications in data engineering or related fields. Strong analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaborating with cross-functional teams and troubleshooting issues. These skills and qualities are important to ensure accurate, reliable, and scalable data pipelines that support critical business analytics and decision-making.
What are popular job titles related to Data Collection Engineer jobs in California? For Data Collection Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Collection Engineer jobs in California look for? The top searched job categories for Data Collection Engineer jobs in California are:
Head of AI Data Collection & Operations , Frontier AI & Robotics

Head of AI Data Collection & Operations , Frontier AI & Robotics

Amazon

San Francisco, CA

Full-time

Re-posted 22 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,974 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Join Amazon's Frontier AI & Robotics team and lead the laboratory operations that enable breakthrough research in embodied intelligence. As Head of Lab Operations, you'll lead the on-the-ground teams that power our AI research programs-directing a large contractor workforce, managing our robot fleet, overseeing data collection campaigns, and ensuring our test environments give researchers and engineers the high-quality operational foundation they need to move fast. Your leadership directly shapes the velocity and quality of our AI research by keeping robots healthy, data pipelines flowing, and test environments ready to support the next wave of innovation.
Key job responsibilities
Lead, develop, and retain a 40-50 person contractor workforce spanning robot fleet operations, AI data collection, and test environment construction; establish clear performance expectations, career development pathways, and a culture of ownership, safety, and continuous improvement
Own robot fleet management end-to-end-maintain robot health and readiness, drive preventive and corrective maintenance programs, track fleet utilization and uptime KPIs, and ensure robots are mission-ready to support research and data collection operations at all times
Direct data collection operations that feed AI research pipelines; coordinate with AI researchers and data engineering teams to plan, execute, and quality-assure data collection campaigns, ensuring operational fidelity and data integrity at scale
Develop, build out, and sustain test environments and experimental infrastructure that enable researchers and engineers to evaluate robotic systems efficiently; manage test cell configuration, instrumentation readiness, and environment lifecycle from initial buildout through ongoing operations
Define, track, and report operational KPIs-including robot fleet uptime, data collection throughput, test environment availability, safety performance, and cost efficiency-using metrics to drive decisions and communicate operational health to senior leadership
Scale operational processes, standard operating procedures (SOPs), and workforce capabilities as research programs grow; build infrastructure and playbooks that maintain quality and speed as scope expands
A day in the life
As the Head of AI Data Collection & Operations at FAR, you set strategic direction for the operational capabilities that drive research velocity: shaping how the organization manages its robot fleet, structures its data collection programs, and builds the infrastructure that gives researchers the freedom to innovate without friction

You are a key voice in senior leadership forums, translating operational performance into strategic insights, championing investments that build long-term organizational capability, and ensuring that lab operations function as a genuine competitive advantage. You invest in your team's growth, forge deep partnerships with research and engineering leadership, and make the resource allocation decisions that keep FAR's operational foundation ahead of an ambitious and fast-moving research roadmap. You define, develop, and drive improvement on key lab performance indicators to ensure we are operating at maximum velocity and efficiency.
About the team
At Frontier AI & Robotics, we're not just advancing robotics - we're reimagining it from the ground up

Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios.
What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models

Our work spans the full spectrum of robotics intelligence - from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Amazon logo

About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US